Overview

Dataset statistics

Number of variables30
Number of observations84
Missing cells928
Missing cells (%)36.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.3 KiB
Average record size in memory259.6 B

Variable types

Numeric10
Categorical10
Unsupported7
Text3

Dataset

Description6270000_대구광역시_08_26_01_P_다단계판매업체_11월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000078044&dataSetDetailId=DDI_0000078072&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
개방자치단체코드 has constant value ""Constant
업종구분명 has constant value ""Constant
상세영업상태코드 is highly imbalanced (54.5%)Imbalance
데이터갱신구분 is highly imbalanced (67.4%)Imbalance
데이터갱신일자 is highly imbalanced (80.2%)Imbalance
인허가취소일자 has 84 (100.0%) missing valuesMissing
폐업일자 has 53 (63.1%) missing valuesMissing
휴업시작일자 has 84 (100.0%) missing valuesMissing
휴업종료일자 has 84 (100.0%) missing valuesMissing
재개업일자 has 84 (100.0%) missing valuesMissing
소재지전화 has 3 (3.6%) missing valuesMissing
소재지면적 has 84 (100.0%) missing valuesMissing
소재지우편번호 has 77 (91.7%) missing valuesMissing
도로명전체주소 has 69 (82.1%) missing valuesMissing
도로명우편번호 has 84 (100.0%) missing valuesMissing
업태구분명 has 84 (100.0%) missing valuesMissing
좌표정보(X) has 69 (82.1%) missing valuesMissing
좌표정보(Y) has 69 (82.1%) missing valuesMissing
번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
도로명우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
자본금의규모 has 5 (6.0%) zerosZeros

Reproduction

Analysis started2024-04-18 01:04:37.083723
Analysis finished2024-04-18 01:04:37.372853
Duration0.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.5
Minimum1
Maximum84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-04-18T10:04:37.431446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.15
Q121.75
median42.5
Q363.25
95-th percentile79.85
Maximum84
Range83
Interquartile range (IQR)41.5

Descriptive statistics

Standard deviation24.392622
Coefficient of variation (CV)0.57394404
Kurtosis-1.2
Mean42.5
Median Absolute Deviation (MAD)21
Skewness0
Sum3570
Variance595
MonotonicityStrictly increasing
2024-04-18T10:04:37.546717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
55 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
Other values (74) 74
88.1%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
다단계판매업체
84 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row다단계판매업체
2nd row다단계판매업체
3rd row다단계판매업체
4th row다단계판매업체
5th row다단계판매업체

Common Values

ValueCountFrequency (%)
다단계판매업체 84
100.0%

Length

2024-04-18T10:04:37.656098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:04:37.731741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다단계판매업체 84
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
08_26_01_P
84 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row08_26_01_P
2nd row08_26_01_P
3rd row08_26_01_P
4th row08_26_01_P
5th row08_26_01_P

Common Values

ValueCountFrequency (%)
08_26_01_P 84
100.0%

Length

2024-04-18T10:04:37.811477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:04:37.885054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
08_26_01_p 84
100.0%

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
6270000
84 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6270000
2nd row6270000
3rd row6270000
4th row6270000
5th row6270000

Common Values

ValueCountFrequency (%)
6270000 84
100.0%

Length

2024-04-18T10:04:37.961911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:04:38.039729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
6270000 84
100.0%

관리번호
Real number (ℝ)

Distinct8
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0063651 × 1019
Minimum2.004627 × 1019
Maximum2.019627 × 1019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-04-18T10:04:38.108412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.004627 × 1019
5-th percentile2.004627 × 1019
Q12.004627 × 1019
median2.004627 × 1019
Q32.004627 × 1019
95-th percentile2.015627 × 1019
Maximum2.019627 × 1019
Range1.5 × 1017
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.9882933 × 1016
Coefficient of variation (CV)0.0019878203
Kurtosis2.3879936
Mean2.0063651 × 1019
Median Absolute Deviation (MAD)0
Skewness1.9942771
Sum1.6853467 × 1021
Variance1.5906483 × 1033
MonotonicityNot monotonic
2024-04-18T10:04:38.215064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2.0046270000041e+19 70
83.3%
2.0136270000041e+19 6
 
7.1%
2.0156270000041e+19 2
 
2.4%
2.0166270000041e+19 2
 
2.4%
2.0176270000041e+19 1
 
1.2%
2.0196270000041e+19 1
 
1.2%
2.0146270000041e+19 1
 
1.2%
2.0126270000041e+19 1
 
1.2%
ValueCountFrequency (%)
2.0046270000041e+19 70
83.3%
2.0126270000041e+19 1
 
1.2%
2.0136270000041e+19 6
 
7.1%
2.0146270000041e+19 1
 
1.2%
2.0156270000041e+19 2
 
2.4%
2.0166270000041e+19 2
 
2.4%
2.0176270000041e+19 1
 
1.2%
2.0196270000041e+19 1
 
1.2%
ValueCountFrequency (%)
2.0196270000041e+19 1
 
1.2%
2.0176270000041e+19 1
 
1.2%
2.0166270000041e+19 2
 
2.4%
2.0156270000041e+19 2
 
2.4%
2.0146270000041e+19 1
 
1.2%
2.0136270000041e+19 6
 
7.1%
2.0126270000041e+19 1
 
1.2%
2.0046270000041e+19 70
83.3%

인허가일자
Real number (ℝ)

Distinct72
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20030377
Minimum19950724
Maximum20190215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-04-18T10:04:38.328536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950724
5-th percentile19962486
Q120001194
median20020130
Q320020858
95-th percentile20148998
Maximum20190215
Range239491
Interquartile range (IQR)19664

Descriptive statistics

Standard deviation54580.081
Coefficient of variation (CV)0.0027248654
Kurtosis0.92904822
Mean20030377
Median Absolute Deviation (MAD)14490
Skewness1.3028109
Sum1.6825516 × 109
Variance2.9789852 × 109
MonotonicityNot monotonic
2024-04-18T10:04:38.450722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20010716 3
 
3.6%
20020617 3
 
3.6%
20020130 3
 
3.6%
20030210 2
 
2.4%
20000308 2
 
2.4%
20040726 2
 
2.4%
20130819 2
 
2.4%
20020309 2
 
2.4%
20020416 2
 
2.4%
20020208 1
 
1.2%
Other values (62) 62
73.8%
ValueCountFrequency (%)
19950724 1
1.2%
19950805 1
1.2%
19951028 1
1.2%
19961105 1
1.2%
19961122 1
1.2%
19970214 1
1.2%
19970313 1
1.2%
19970529 1
1.2%
19971220 1
1.2%
19980320 1
1.2%
ValueCountFrequency (%)
20190215 1
1.2%
20161122 1
1.2%
20160502 1
1.2%
20150511 1
1.2%
20150422 1
1.2%
20140929 1
1.2%
20131023 1
1.2%
20131022 1
1.2%
20130819 2
2.4%
20130619 1
1.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

영업상태구분코드
Categorical

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
3
61 
4
20 
1
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
3 61
72.6%
4 20
 
23.8%
1 3
 
3.6%

Length

2024-04-18T10:04:38.568057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:04:38.655528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 61
72.6%
4 20
 
23.8%
1 3
 
3.6%

영업상태명
Categorical

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
폐업
61 
취소/말소/만료/정지/중지
20 
영업/정상
 
3

Length

Max length14
Median length2
Mean length4.9642857
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row취소/말소/만료/정지/중지
3rd row취소/말소/만료/정지/중지
4th row취소/말소/만료/정지/중지
5th row취소/말소/만료/정지/중지

Common Values

ValueCountFrequency (%)
폐업 61
72.6%
취소/말소/만료/정지/중지 20
 
23.8%
영업/정상 3
 
3.6%

Length

2024-04-18T10:04:38.748645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:04:38.842990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 61
72.6%
취소/말소/만료/정지/중지 20
 
23.8%
영업/정상 3
 
3.6%

상세영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
4
61 
6
20 
2
 
1
BBBB
 
1
1
 
1

Length

Max length4
Median length1
Mean length1.0357143
Min length1

Unique

Unique3 ?
Unique (%)3.6%

Sample

1st row2
2nd row6
3rd row6
4th row6
5th row6

Common Values

ValueCountFrequency (%)
4 61
72.6%
6 20
 
23.8%
2 1
 
1.2%
BBBB 1
 
1.2%
1 1
 
1.2%

Length

2024-04-18T10:04:38.937598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:04:39.029462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 61
72.6%
6 20
 
23.8%
2 1
 
1.2%
bbbb 1
 
1.2%
1 1
 
1.2%

상세영업상태명
Categorical

Distinct3
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size804.0 B
폐업
61 
직권말소
20 
영업
 
3

Length

Max length4
Median length2
Mean length2.4761905
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업
2nd row직권말소
3rd row직권말소
4th row직권말소
5th row직권말소

Common Values

ValueCountFrequency (%)
폐업 61
72.6%
직권말소 20
 
23.8%
영업 3
 
3.6%

Length

2024-04-18T10:04:39.136707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:04:39.230994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 61
72.6%
직권말소 20
 
23.8%
영업 3
 
3.6%

폐업일자
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)77.4%
Missing53
Missing (%)63.1%
Infinite0
Infinite (%)0.0%
Mean20102218
Minimum19970331
Maximum20181018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-04-18T10:04:39.318512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970331
5-th percentile20010861
Q120025664
median20140501
Q320180514
95-th percentile20180721
Maximum20181018
Range210687
Interquartile range (IQR)154850.5

Descriptive statistics

Standard deviation75538.355
Coefficient of variation (CV)0.0037577125
Kurtosis-1.8082954
Mean20102218
Median Absolute Deviation (MAD)40230
Skewness-0.20663621
Sum6.2316876 × 108
Variance5.7060431 × 109
MonotonicityNot monotonic
2024-04-18T10:04:39.430043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
20180514 7
 
8.3%
20140501 2
 
2.4%
20041229 1
 
1.2%
20031105 1
 
1.2%
20040211 1
 
1.2%
20010502 1
 
1.2%
20030106 1
 
1.2%
20021209 1
 
1.2%
20030130 1
 
1.2%
20020522 1
 
1.2%
Other values (14) 14
 
16.7%
(Missing) 53
63.1%
ValueCountFrequency (%)
19970331 1
1.2%
20010502 1
1.2%
20011220 1
1.2%
20020110 1
1.2%
20020306 1
1.2%
20020522 1
1.2%
20021209 1
1.2%
20021221 1
1.2%
20030106 1
1.2%
20030130 1
1.2%
ValueCountFrequency (%)
20181018 1
 
1.2%
20180731 1
 
1.2%
20180711 1
 
1.2%
20180514 7
8.3%
20180131 1
 
1.2%
20151203 1
 
1.2%
20150302 1
 
1.2%
20140926 1
 
1.2%
20140623 1
 
1.2%
20140501 2
 
2.4%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

소재지전화
Real number (ℝ)

MISSING 

Distinct81
Distinct (%)100.0%
Missing3
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean5.0946686 × 108
Minimum15449886
Maximum8.0896889 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-04-18T10:04:39.550580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15449886
5-th percentile18997889
Q15.3422904 × 108
median5.3652336 × 108
Q35.3751744 × 108
95-th percentile5.3956953 × 108
Maximum8.0896889 × 108
Range7.93519 × 108
Interquartile range (IQR)3288395

Descriptive statistics

Standard deviation1.3187339 × 108
Coefficient of variation (CV)0.25884587
Kurtosis10.374102
Mean5.0946686 × 108
Median Absolute Deviation (MAD)1030560
Skewness-3.1305607
Sum4.1266816 × 1010
Variance1.7390592 × 1016
MonotonicityNot monotonic
2024-04-18T10:04:39.677612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
534318900 1
 
1.2%
537565050 1
 
1.2%
534210622 1
 
1.2%
537426258 1
 
1.2%
537456367 1
 
1.2%
532541728 1
 
1.2%
532569173 1
 
1.2%
537450034 1
 
1.2%
532471234 1
 
1.2%
535738003 1
 
1.2%
Other values (71) 71
84.5%
(Missing) 3
 
3.6%
ValueCountFrequency (%)
15449886 1
1.2%
16660223 1
1.2%
16668118 1
1.2%
18993121 1
1.2%
18997889 1
1.2%
531661688 1
1.2%
532471234 1
1.2%
532475660 1
1.2%
532537180 1
1.2%
532541728 1
1.2%
ValueCountFrequency (%)
808968888 1
1.2%
704760398 1
1.2%
539637779 1
1.2%
539626200 1
1.2%
539569534 1
1.2%
539431472 1
1.2%
537612109 1
1.2%
537610040 1
1.2%
537579058 1
1.2%
537565050 1
1.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct7
Distinct (%)100.0%
Missing77
Missing (%)91.7%
Infinite0
Infinite (%)0.0%
Mean513443.57
Minimum41166
Maximum705808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-04-18T10:04:39.777867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41166
5-th percentile41458.8
Q1371277
median701021
Q3701778
95-th percentile704613.7
Maximum705808
Range664642
Interquartile range (IQR)330501

Descriptive statistics

Standard deviation322298.4
Coefficient of variation (CV)0.62771922
Kurtosis-0.8400749
Mean513443.57
Median Absolute Deviation (MAD)806
Skewness-1.2295131
Sum3594105
Variance1.0387626 × 1011
MonotonicityNot monotonic
2024-04-18T10:04:39.866760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
42142 1
 
1.2%
41166 1
 
1.2%
705808 1
 
1.2%
701021 1
 
1.2%
701729 1
 
1.2%
701827 1
 
1.2%
700412 1
 
1.2%
(Missing) 77
91.7%
ValueCountFrequency (%)
41166 1
1.2%
42142 1
1.2%
700412 1
1.2%
701021 1
1.2%
701729 1
1.2%
701827 1
1.2%
705808 1
1.2%
ValueCountFrequency (%)
705808 1
1.2%
701827 1
1.2%
701729 1
1.2%
701021 1
1.2%
700412 1
1.2%
42142 1
1.2%
41166 1
1.2%

소재지전체주소
Text

Distinct81
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-04-18T10:04:40.135350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length32.5
Mean length28.130952
Min length1

Characters and Unicode

Total characters2363
Distinct characters123
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)94.0%

Sample

1st row대구광역시 동구 신천동 74번지 1호 74번지 1호 74번지 1호
2nd row대구광역시 서구 내당동 230번지 1호 301호
3rd row대구광역시 수성구 수성동1가 272번지 11호 한가라코아상가 202호
4th row대구광역시 동구 신천동 323-3
5th row대구광역시 동구 신천동 391-2
ValueCountFrequency (%)
대구광역시 81
 
18.2%
동구 26
 
5.9%
신천동 22
 
5.0%
수성구 16
 
3.6%
중구 14
 
3.2%
남구 10
 
2.3%
대명동 8
 
1.8%
서구 8
 
1.8%
4층 7
 
1.6%
2층 7
 
1.6%
Other values (175) 245
55.2%
2024-04-18T10:04:40.568470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
606
25.6%
구 163
 
6.9%
동 144
 
6.1%
대 102
 
4.3%
1 97
 
4.1%
광 87
 
3.7%
역 81
 
3.4%
시 81
 
3.4%
3 67
 
2.8%
- 60
 
2.5%
Other values (113) 875
37.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1224
51.8%
Space Separator 606
25.6%
Decimal Number 452
 
19.1%
Dash Punctuation 60
 
2.5%
Open Punctuation 9
 
0.4%
Close Punctuation 9
 
0.4%
Uppercase Letter 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 163
 
13.3%
동 144
 
11.8%
대 102
 
8.3%
광 87
 
7.1%
역 81
 
6.6%
시 81
 
6.6%
층 41
 
3.3%
신 36
 
2.9%
빌 33
 
2.7%
천 33
 
2.7%
Other values (96) 423
34.6%
Decimal Number
ValueCountFrequency (%)
1 97
21.5%
3 67
14.8%
2 60
13.3%
4 42
9.3%
7 41
9.1%
0 33
 
7.3%
6 31
 
6.9%
5 31
 
6.9%
8 25
 
5.5%
9 25
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
O 1
50.0%
Space Separator
ValueCountFrequency (%)
606
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1224
51.8%
Common 1137
48.1%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 163
 
13.3%
동 144
 
11.8%
대 102
 
8.3%
광 87
 
7.1%
역 81
 
6.6%
시 81
 
6.6%
층 41
 
3.3%
신 36
 
2.9%
빌 33
 
2.7%
천 33
 
2.7%
Other values (96) 423
34.6%
Common
ValueCountFrequency (%)
606
53.3%
1 97
 
8.5%
3 67
 
5.9%
- 60
 
5.3%
2 60
 
5.3%
4 42
 
3.7%
7 41
 
3.6%
0 33
 
2.9%
6 31
 
2.7%
5 31
 
2.7%
Other values (5) 69
 
6.1%
Latin
ValueCountFrequency (%)
T 1
50.0%
O 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1224
51.8%
ASCII 1139
48.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
606
53.2%
1 97
 
8.5%
3 67
 
5.9%
- 60
 
5.3%
2 60
 
5.3%
4 42
 
3.7%
7 41
 
3.6%
0 33
 
2.9%
6 31
 
2.7%
5 31
 
2.7%
Other values (7) 71
 
6.2%
Hangul
ValueCountFrequency (%)
구 163
 
13.3%
동 144
 
11.8%
대 102
 
8.3%
광 87
 
7.1%
역 81
 
6.6%
시 81
 
6.6%
층 41
 
3.3%
신 36
 
2.9%
빌 33
 
2.7%
천 33
 
2.7%
Other values (96) 423
34.6%

도로명전체주소
Text

MISSING 

Distinct13
Distinct (%)86.7%
Missing69
Missing (%)82.1%
Memory size804.0 B
2024-04-18T10:04:40.744886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length28
Mean length26.266667
Min length21

Characters and Unicode

Total characters394
Distinct characters63
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)73.3%

Sample

1st row대구광역시 동구 동대구로 503 (신천동)
2nd row대구광역시 서구 서대구로 38, 301호 (내당동)
3rd row대구광역시 수성구 명덕로 368, 202호 (수성동1가,한가라코아상가)
4th row대구광역시 수성구 들안로 236 (수성동3가)
5th row대구광역시 동구 화랑로 471 (용계동)
ValueCountFrequency (%)
대구광역시 15
18.8%
동구 8
 
10.0%
신천동 6
 
7.5%
수성구 4
 
5.0%
66 2
 
2.5%
2층 2
 
2.5%
동대구로 2
 
2.5%
동부로26길 2
 
2.5%
용계동 2
 
2.5%
471 2
 
2.5%
Other values (34) 35
43.8%
2024-04-18T10:04:41.020810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
65
16.5%
구 33
 
8.4%
동 28
 
7.1%
대 19
 
4.8%
( 15
 
3.8%
광 15
 
3.8%
역 15
 
3.8%
시 15
 
3.8%
로 15
 
3.8%
) 15
 
3.8%
Other values (53) 159
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 229
58.1%
Space Separator 65
 
16.5%
Decimal Number 62
 
15.7%
Open Punctuation 15
 
3.8%
Close Punctuation 15
 
3.8%
Other Punctuation 7
 
1.8%
Dash Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 33
14.4%
동 28
12.2%
대 19
 
8.3%
광 15
 
6.6%
역 15
 
6.6%
시 15
 
6.6%
로 15
 
6.6%
성 8
 
3.5%
수 8
 
3.5%
가 7
 
3.1%
Other values (38) 66
28.8%
Decimal Number
ValueCountFrequency (%)
2 12
19.4%
6 10
16.1%
3 9
14.5%
1 7
11.3%
0 6
9.7%
4 5
8.1%
8 5
8.1%
7 3
 
4.8%
5 3
 
4.8%
9 2
 
3.2%
Space Separator
ValueCountFrequency (%)
65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 229
58.1%
Common 165
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 33
14.4%
동 28
12.2%
대 19
 
8.3%
광 15
 
6.6%
역 15
 
6.6%
시 15
 
6.6%
로 15
 
6.6%
성 8
 
3.5%
수 8
 
3.5%
가 7
 
3.1%
Other values (38) 66
28.8%
Common
ValueCountFrequency (%)
65
39.4%
( 15
 
9.1%
) 15
 
9.1%
2 12
 
7.3%
6 10
 
6.1%
3 9
 
5.5%
, 7
 
4.2%
1 7
 
4.2%
0 6
 
3.6%
4 5
 
3.0%
Other values (5) 14
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 229
58.1%
ASCII 165
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
65
39.4%
( 15
 
9.1%
) 15
 
9.1%
2 12
 
7.3%
6 10
 
6.1%
3 9
 
5.5%
, 7
 
4.2%
1 7
 
4.2%
0 6
 
3.6%
4 5
 
3.0%
Other values (5) 14
 
8.5%
Hangul
ValueCountFrequency (%)
구 33
14.4%
동 28
12.2%
대 19
 
8.3%
광 15
 
6.6%
역 15
 
6.6%
시 15
 
6.6%
로 15
 
6.6%
성 8
 
3.5%
수 8
 
3.5%
가 7
 
3.1%
Other values (38) 66
28.8%

도로명우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

사업장명
Text

Distinct83
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size804.0 B
2024-04-18T10:04:41.214158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length8.3452381
Min length5

Characters and Unicode

Total characters701
Distinct characters164
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)97.6%

Sample

1st row(주)투에버
2nd row주식회사 예스인포
3rd row주식회사 아이시냅스
4th row(주)밀레니스
5th row(주)아프로드
ValueCountFrequency (%)
주식회사 8
 
8.6%
주)그린앤센스 2
 
2.2%
네오슈머네트워크(주 1
 
1.1%
주)알.엠.더블유 1
 
1.1%
굿패밀리꼬레아(주 1
 
1.1%
엔터프라이즈 1
 
1.1%
주)엔브이케이 1
 
1.1%
주)해피젠 1
 
1.1%
주)케이.에이치.디 1
 
1.1%
주)바이오이라이프 1
 
1.1%
Other values (75) 75
80.6%
2024-04-18T10:04:41.519810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 83
 
11.8%
( 75
 
10.7%
) 75
 
10.7%
이 33
 
4.7%
아 16
 
2.3%
리 16
 
2.3%
스 13
 
1.9%
코 13
 
1.9%
인 11
 
1.6%
라 10
 
1.4%
Other values (154) 356
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 538
76.7%
Open Punctuation 75
 
10.7%
Close Punctuation 75
 
10.7%
Space Separator 9
 
1.3%
Other Punctuation 4
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 83
 
15.4%
이 33
 
6.1%
아 16
 
3.0%
리 16
 
3.0%
스 13
 
2.4%
코 13
 
2.4%
인 11
 
2.0%
라 10
 
1.9%
터 9
 
1.7%
사 8
 
1.5%
Other values (150) 326
60.6%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 538
76.7%
Common 163
 
23.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 83
 
15.4%
이 33
 
6.1%
아 16
 
3.0%
리 16
 
3.0%
스 13
 
2.4%
코 13
 
2.4%
인 11
 
2.0%
라 10
 
1.9%
터 9
 
1.7%
사 8
 
1.5%
Other values (150) 326
60.6%
Common
ValueCountFrequency (%)
( 75
46.0%
) 75
46.0%
9
 
5.5%
. 4
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 538
76.7%
ASCII 163
 
23.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 83
 
15.4%
이 33
 
6.1%
아 16
 
3.0%
리 16
 
3.0%
스 13
 
2.4%
코 13
 
2.4%
인 11
 
2.0%
라 10
 
1.9%
터 9
 
1.7%
사 8
 
1.5%
Other values (150) 326
60.6%
ASCII
ValueCountFrequency (%)
( 75
46.0%
) 75
46.0%
9
 
5.5%
. 4
 
2.5%

최종수정시점
Real number (ℝ)

Distinct18
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0142818 × 1013
Minimum2.005111 × 1013
Maximum2.0190215 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-04-18T10:04:41.624949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.005111 × 1013
5-th percentile2.005111 × 1013
Q12.0141001 × 1013
median2.0141001 × 1013
Q32.0180514 × 1013
95-th percentile2.0188745 × 1013
Maximum2.0190215 × 1013
Range1.39105 × 1011
Interquartile range (IQR)3.9513 × 1010

Descriptive statistics

Standard deviation4.531384 × 1010
Coefficient of variation (CV)0.0022496276
Kurtosis0.18762799
Mean2.0142818 × 1013
Median Absolute Deviation (MAD)3.9513 × 1010
Skewness-1.1556082
Sum1.6919968 × 1015
Variance2.0533441 × 1021
MonotonicityNot monotonic
2024-04-18T10:04:41.716275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
20141001000000 32
38.1%
20180514000000 25
29.8%
20051110000000 7
 
8.3%
20051111000000 5
 
6.0%
20051112000000 2
 
2.4%
20151204000000 1
 
1.2%
20150304000000 1
 
1.2%
20181018000000 1
 
1.2%
20140623000000 1
 
1.2%
20140926000000 1
 
1.2%
Other values (8) 8
 
9.5%
ValueCountFrequency (%)
20051110000000 7
 
8.3%
20051111000000 5
 
6.0%
20051112000000 2
 
2.4%
20140623000000 1
 
1.2%
20140926000000 1
 
1.2%
20141001000000 32
38.1%
20150304000000 1
 
1.2%
20151204000000 1
 
1.2%
20180131000000 1
 
1.2%
20180514000000 25
29.8%
ValueCountFrequency (%)
20190215000000 1
 
1.2%
20190124000000 1
 
1.2%
20190115000000 1
 
1.2%
20190110000000 1
 
1.2%
20190109000000 1
 
1.2%
20181018000000 1
 
1.2%
20180731000000 1
 
1.2%
20180711000000 1
 
1.2%
20180514000000 25
29.8%
20180131000000 1
 
1.2%

데이터갱신구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
I
79 
U
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowU
2nd rowI
3rd rowU
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 79
94.0%
U 5
 
6.0%

Length

2024-04-18T10:04:41.823411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:04:41.903209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 79
94.0%
u 5
 
6.0%

데이터갱신일자
Categorical

IMBALANCE 

Distinct7
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size804.0 B
2018-08-31 23:59:59.0
78 
2019-01-26 02:40:00.0
 
1
2019-01-11 02:40:00.0
 
1
2019-01-12 02:40:00.0
 
1
2019-01-17 02:40:00.0
 
1
Other values (2)
 
2

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique6 ?
Unique (%)7.1%

Sample

1st row2019-01-26 02:40:00.0
2nd row2018-08-31 23:59:59.0
3rd row2019-01-11 02:40:00.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 78
92.9%
2019-01-26 02:40:00.0 1
 
1.2%
2019-01-11 02:40:00.0 1
 
1.2%
2019-01-12 02:40:00.0 1
 
1.2%
2019-01-17 02:40:00.0 1
 
1.2%
2019-02-17 02:21:23.0 1
 
1.2%
2018-10-20 02:37:50.0 1
 
1.2%

Length

2024-04-18T10:04:41.980093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:04:42.070663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018-08-31 78
46.4%
23:59:59.0 78
46.4%
02:40:00.0 4
 
2.4%
2019-01-26 1
 
0.6%
2019-01-11 1
 
0.6%
2019-01-12 1
 
0.6%
2019-01-17 1
 
0.6%
2019-02-17 1
 
0.6%
02:21:23.0 1
 
0.6%
2018-10-20 1
 
0.6%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing84
Missing (%)100.0%
Memory size888.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)93.3%
Missing69
Missing (%)82.1%
Infinite0
Infinite (%)0.0%
Mean346325.27
Minimum340568.71
Maximum351231.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-04-18T10:04:42.164088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum340568.71
5-th percentile342008.36
Q1345036.66
median346671.75
Q3346954.22
95-th percentile351217.35
Maximum351231.86
Range10663.147
Interquartile range (IQR)1917.5643

Descriptive statistics

Standard deviation2751.8667
Coefficient of variation (CV)0.0079459021
Kurtosis0.94627786
Mean346325.27
Median Absolute Deviation (MAD)1284.6914
Skewness-0.043040743
Sum5194879
Variance7572770.1
MonotonicityNot monotonic
2024-04-18T10:04:42.251944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
346954.221839 2
 
2.4%
346691.95191 1
 
1.2%
340568.709643 1
 
1.2%
345387.055812 1
 
1.2%
344686.259338 1
 
1.2%
351231.856724 1
 
1.2%
351211.131308 1
 
1.2%
348061.829692 1
 
1.2%
342625.355314 1
 
1.2%
345727.539482 1
 
1.2%
Other values (4) 4
 
4.8%
(Missing) 69
82.1%
ValueCountFrequency (%)
340568.709643 1
1.2%
342625.355314 1
1.2%
344634.648244 1
1.2%
344686.259338 1
1.2%
345387.055812 1
1.2%
345727.539482 1
1.2%
346557.305781 1
1.2%
346671.747221 1
1.2%
346691.95191 1
1.2%
346915.153894 1
1.2%
ValueCountFrequency (%)
351231.856724 1
1.2%
351211.131308 1
1.2%
348061.829692 1
1.2%
346954.221839 2
2.4%
346915.153894 1
1.2%
346691.95191 1
1.2%
346671.747221 1
1.2%
346557.305781 1
1.2%
345727.539482 1
1.2%
345387.055812 1
1.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)93.3%
Missing69
Missing (%)82.1%
Infinite0
Infinite (%)0.0%
Mean264191.26
Minimum261396.15
Maximum265256.54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-04-18T10:04:42.344638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum261396.15
5-th percentile262364.69
Q1263713.19
median264539.57
Q3265013.71
95-th percentile265253.34
Maximum265256.54
Range3860.3947
Interquartile range (IQR)1300.5186

Descriptive statistics

Standard deviation1107.8879
Coefficient of variation (CV)0.0041935071
Kurtosis1.4593445
Mean264191.26
Median Absolute Deviation (MAD)580.69246
Skewness-1.3108031
Sum3962868.9
Variance1227415.6
MonotonicityNot monotonic
2024-04-18T10:04:42.438348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
264539.57332 2
 
2.4%
265138.774608 1
 
1.2%
263467.493083 1
 
1.2%
262779.774089 1
 
1.2%
263958.880864 1
 
1.2%
265251.965461 1
 
1.2%
265256.542723 1
 
1.2%
264922.921495 1
 
1.2%
261396.148029 1
 
1.2%
263045.110029 1
 
1.2%
Other values (4) 4
 
4.8%
(Missing) 69
82.1%
ValueCountFrequency (%)
261396.148029 1
1.2%
262779.774089 1
1.2%
263045.110029 1
1.2%
263467.493083 1
1.2%
263958.880864 1
1.2%
263978.051871 1
1.2%
264539.57332 2
2.4%
264572.308083 1
1.2%
264917.244196 1
1.2%
264922.921495 1
1.2%
ValueCountFrequency (%)
265256.542723 1
1.2%
265251.965461 1
1.2%
265138.774608 1
1.2%
265104.489673 1
1.2%
264922.921495 1
1.2%
264917.244196 1
1.2%
264572.308083 1
1.2%
264539.57332 2
2.4%
263978.051871 1
1.2%
263958.880864 1
1.2%

업종구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
다단계판매업
84 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row다단계판매업
2nd row다단계판매업
3rd row다단계판매업
4th row다단계판매업
5th row다단계판매업

Common Values

ValueCountFrequency (%)
다단계판매업 84
100.0%

Length

2024-04-18T10:04:42.534743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:04:42.611737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다단계판매업 84
100.0%

자본금의규모
Real number (ℝ)

ZEROS 

Distinct46
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7874843 × 108
Minimum0
Maximum2.06 × 1010
Zeros5
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2024-04-18T10:04:42.706101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4602885.2
Q13 × 108
median3.0910483 × 108
Q35 × 108
95-th percentile5.2379556 × 108
Maximum2.06 × 1010
Range2.06 × 1010
Interquartile range (IQR)2 × 108

Descriptive statistics

Standard deviation2.2152213 × 109
Coefficient of variation (CV)3.8276066
Kurtosis83.309706
Mean5.7874843 × 108
Median Absolute Deviation (MAD)9104831.5
Skewness9.1090977
Sum4.8614868 × 1010
Variance4.9072054 × 1018
MonotonicityNot monotonic
2024-04-18T10:04:42.820649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
300000000 18
21.4%
500000000 13
 
15.5%
0 5
 
6.0%
310000000 5
 
6.0%
505000000 2
 
2.4%
20600000000 1
 
1.2%
550000000 1
 
1.2%
303340000 1
 
1.2%
320000000 1
 
1.2%
308209663 1
 
1.2%
Other values (36) 36
42.9%
ValueCountFrequency (%)
0 5
 
6.0%
30685901 1
 
1.2%
31000000 1
 
1.2%
50000000 1
 
1.2%
300000000 18
21.4%
300143794 1
 
1.2%
300325980 1
 
1.2%
300920500 1
 
1.2%
301872700 1
 
1.2%
302434200 1
 
1.2%
ValueCountFrequency (%)
20600000000 1
 
1.2%
600000000 1
 
1.2%
550000000 1
 
1.2%
530000000 1
 
1.2%
524816089 1
 
1.2%
518012590 1
 
1.2%
515000000 1
 
1.2%
505000000 2
 
2.4%
501000000 1
 
1.2%
500000000 13
15.5%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업종구분명자본금의규모
01다단계판매업체08_26_01_P62700002004627000004100004320110405<NA>1영업/정상2영업<NA><NA><NA><NA>537579058<NA><NA>대구광역시 동구 신천동 74번지 1호 74번지 1호 74번지 1호대구광역시 동구 동대구로 503 (신천동)<NA>(주)투에버20190124000000U2019-01-26 02:40:00.0<NA>346691.95191265138.774608다단계판매업20600000000
12다단계판매업체08_26_01_P62700002017627000004100000120161122<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>16668118<NA><NA>대구광역시 서구 내당동 230번지 1호 301호대구광역시 서구 서대구로 38, 301호 (내당동)<NA>주식회사 예스인포20180514000000I2018-08-31 23:59:59.0<NA>340568.709643263467.493083다단계판매업0
23다단계판매업체08_26_01_P62700002015627000004100000220150511<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>16660223<NA><NA>대구광역시 수성구 수성동1가 272번지 11호 한가라코아상가 202호대구광역시 수성구 명덕로 368, 202호 (수성동1가,한가라코아상가)<NA>주식회사 아이시냅스20190109000000U2019-01-11 02:40:00.0<NA>345387.055812262779.774089다단계판매업500000000
34다단계판매업체08_26_01_P62700002004627000004100006419951028<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>537439866<NA><NA>대구광역시 동구 신천동 323-3<NA><NA>(주)밀레니스20180514000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업330985000
45다단계판매업체08_26_01_P62700002004627000004100006319961105<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>536560755<NA><NA>대구광역시 동구 신천동 391-2<NA><NA>(주)아프로드20180514000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업310223400
56다단계판매업체08_26_01_P62700002004627000004100006119971220<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>534760180<NA><NA>대구광역시 남구 봉덕동 봉덕1동 606-8번지<NA><NA>코리넷(주)20180514000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업492940000
67다단계판매업체08_26_01_P62700002004627000004100005020001130<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>536523360<NA><NA>대구광역시 남구 대명동 대명7동 1896-13 쌍마빌딩2층<NA><NA>(주)옥타코리아20180514000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업302465000
78다단계판매업체08_26_01_P62700002004627000004100004820001223<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>537610040<NA><NA>대구광역시 수성구 수성동3가 332 다송빌딩 2층<NA><NA>(주)지엠코리아원20180514000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업310000000
89다단계판매업체08_26_01_P62700002004627000004100005919970529<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>534740075<NA><NA>대구광역시 남구 봉덕동 봉덕1동 1300-5<NA><NA>(주)보은인터내셔날20180514000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업300000000
910다단계판매업체08_26_01_P62700002004627000004100005720000308<NA>4취소/말소/만료/정지/중지6직권말소<NA><NA><NA><NA>535625042<NA><NA>대구광역시 서구 평리동 평리2동 1097-1 창성빌딩 5층<NA><NA>(주)신기예스20180514000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업300920500
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)업종구분명자본금의규모
7475다단계판매업체08_26_01_P62700002004627000004100000320040726<NA>3폐업4폐업<NA><NA><NA><NA>534742306<NA><NA>대구광역시 남구 대명동 2010-1 남대구보험회관 5층<NA><NA>(주)골든아이20141001000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업530000000
7576다단계판매업체08_26_01_P62700002004627000004100004420010315<NA>3폐업4폐업20040211<NA><NA><NA>534297744<NA><NA>대구광역시 중구 삼덕동2가 210-1 진석타워 5층 7호<NA><NA>(주)리치웨이인터내셔날20051112000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업500000000
7677다단계판매업체08_26_01_P62700002004627000004100000220030210<NA>3폐업4폐업<NA><NA><NA><NA>537543391<NA><NA>대구광역시 중구 동산동 788-5 그룹원빌딩 7층<NA><NA>다부코리아20141001000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업524816089
7778다단계판매업체08_26_01_P62700002004627000004100000620021028<NA>3폐업4폐업<NA><NA><NA><NA>537556251<NA><NA>대구광역시 동구 신천동 신천3동 194-45 목화빌딩 3층<NA><NA>(주)라이프케어코리아20141001000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업31000000
7879다단계판매업체08_26_01_P62700002004627000004100003320011112<NA>3폐업4폐업<NA><NA><NA><NA>536562861<NA><NA>대구광역시 남구 대명동 대명2동 1790-3 한빛은행 2층<NA><NA>(주)프리웨이20141001000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업354742703
7980다단계판매업체08_26_01_P62700002004627000004100003720010716<NA>3폐업4폐업20031105<NA><NA><NA>539569534<NA><NA>대구광역시 북구 서변동 970번지 (2층)<NA><NA>(주)골든임페리얼20051110000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업304599000
8081다단계판매업체08_26_01_P62700002004627000004100004220010420<NA>3폐업4폐업20180514<NA><NA><NA>534220330<NA><NA>대구광역시 북구 침산동 심산2동 156-50<NA><NA>(주)라이즈업20180514000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업308022975
8182다단계판매업체08_26_01_P62700002004627000004100006819980320<NA>3폐업4폐업20180514<NA><NA><NA>537517435<NA><NA>대구광역시 수성구 범어동 186-4번지<NA><NA>(주)제이아이씨20180514000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업306493677
8283다단계판매업체08_26_01_P62700002004627000004100006720000308<NA>3폐업4폐업20180514<NA><NA><NA>536234400<NA><NA>대구광역시 달서구 두류동 8-7-3 한신빌딩 6층<NA><NA>케이제이엠종합유통(주)20180514000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업300000000
8384다단계판매업체08_26_01_P62700002004627000004100006619950805<NA>3폐업4폐업<NA><NA><NA><NA>537521030<NA><NA>대구광역시 동구 신천동 신천4동 335-6<NA><NA>(주)세비앙몽드20141001000000I2018-08-31 23:59:59.0<NA><NA><NA>다단계판매업306000000